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smaddanki/README.md

Smaddanki Blog Content Repository

About Me

I architect and implement data systems and conduct quantitative research at the intersection of data engineering, machine learning, artificial intelligence, and business intelligence. Through my blog smaddanki.com, I explore the synergy between robust data infrastructure and sophisticated analytical methods. This repository serves as a comprehensive resource hub, combining practical code implementations, detailed technical analyses, and in-depth tutorials across these domains.

Core Focus Areas

  • Applied Machine Learning
  • Time Series, NLP, LLMs, RecSys
  • Quantitative Finance

Connect:

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  1. nlp-llms nlp-llms Public

  2. timeseries timeseries Public

    Time Series Analysis, including detection, forecasting, feature extraction/embedding, multivariate analysis using techniques ranging from traditional ARIMA models to modern neural networks.

  3. recsys recsys Public

    An implementation of a various recommendation system models from content based to deep learning

    Python

  4. data-science data-science Public

    Code blocks, algorithms, and research snippets in Data Science, Machine Learning, AI & Quant Finance.

    Jupyter Notebook

  5. mlops mlops Public

    Shell